Signal processing method and imaging system for scatter correction in computed tomography

ABSTRACT

A signal processing method is disclosed, which includes detecting a total intensity of X-rays passing through an object comprising multiple materials; obtaining at least one set of basis information of basis material information of the multiple materials and basis component information of photon-electric absorption basis component and Compton scattering basis component of the object; estimating a scatter intensity component of the detected X-rays based on the at least one set of basis information and the detected total intensity; and obtaining an intensity estimate of primary X-rays incident on a detector based on the detected total intensity and the estimated scatter intensity component. An imaging system adopting the above signal processing method is also disclosed.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to and the benefit of U.S. patentapplication Ser. No. 15/263,565, entitled “SIGNAL PROCESSING METHOD ANDIMAGING SYSTEM FOR SCATTER CORRECTION IN COMPUTED TOMOGRAPHY”, filedSep. 13, 2016, which is herein incorporated by reference in itsentirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH & DEVELOPMENT

This invention was made with US Government support under contract number7R01HL111141-02 awarded by the US Department of Health and HumanServices National Institutes of Health. The US Government has certainrights in the invention.

BACKGROUND

This disclosure relates generally to a signal processing technique, andmore particularly to a signal processing method and an imaging systemfor scatter correction in computed tomography.

Non-invasive imaging technologies, such as computed tomography (CT),allow images of internal structures of an object to be obtained withoutperforming an invasive procedure on the object. In a CT imaging system,scatter signal in the X-ray measurement can cause shading artifacts,reduce image resolution, and other artifacts which all degrade imagequality. At the same time, the scatter signal from the object is one ofthe major sources of bias of the quantitative measurements from thereconstructed images of the CT imaging system.

Accordingly, it would be desirable to reduce or eliminate the impact ofscatter from the object that to be measured. Therefore, an improvedscatter correction method would improve CT image quality.

BRIEF DESCRIPTION

In one embodiment, the present disclosure provides a signal processingmethod. The method comprises: detecting a total intensity of X-rayspassing through an object comprising multiple materials; obtaining atleast one set of basis information of basis material information of themultiple materials and basis component information of photon-electricabsorption basis component and Compton scattering basis component of theobject; estimating a scatter intensity component of the detected X-raysbased on the at least one set of basis information and the detectedtotal intensity; and obtaining an intensity estimate of primary X-raysincident on a detector based on the detected total intensity and theestimated scatter intensity component.

In another embodiment, the present disclosure provides an imagingsystem. The system comprises a detector and a computer. The detector isconfigured for detecting a total intensity of X-rays passing through anobject comprising multiple materials. The computer is configured forobtaining at least one set of basis information of basis materialinformation of the multiple materials and basis component information ofphoton-electric absorption basis component and Compton scattering basiscomponent of the object, estimating a scatter intensity component of thedetected X-rays based on the at least one set of basis information andthe detected total intensity, and obtaining an intensity estimate ofprimary X-rays incident on the detector based on the detected totalintensity and the estimated scatter intensity component.

DRAWINGS

These and other features, aspects, and advantages of the presentdisclosure will become better understood when the following detaileddescription is read with reference to the accompanying drawings in whichlike characters represent like parts throughout the drawings, wherein:

FIG. 1 is a schematic block diagram of an exemplary CT imaging system inaccordance with an embodiment of the present disclosure;

FIG. 2 is a schematic block diagram of one embodiment of modulesexecuting in a computer of FIG. 1;

FIG. 3 is a schematic block diagram of another embodiment of modulesexecuting in the computer of FIG. 1;

FIG. 4 is a flow chart of an exemplary signal processing method inaccordance with an embodiment of the present disclosure;

FIG. 5 illustrates steps how to obtain at least one set of basisinformation in accordance with an embodiment of the present disclosure;and

FIG. 6 illustrates steps how to obtain at least one set of basisinformation in accordance with another embodiment of the presentdisclosure.

DETAILED DESCRIPTION

Embodiments of the present disclosure will be described herein belowwith reference to the accompanying drawings. In the followingdescription, well-known functions or constructions are not described indetail to avoid obscuring the disclosure in unnecessary detail.

Unless defined otherwise, technical and scientific terms used hereinhave the same meaning as is commonly understood by one of ordinary skillin the art to which this disclosure belongs. The terms “first”,“second”, “third” and the like, as used herein do not denote any order,quantity, or importance, but rather are used to distinguish one elementfrom another. Also, the terms “a” and “an” do not denote a limitation ofquantity, but rather denote the presence of at least one of thereferenced items. The term “or” is meant to be inclusive and mean eitheror all of the listed items. The use of “including,” “comprising” or“having” and variations thereof herein are meant to encompass the itemslisted thereafter and equivalents thereof as well as additional items.In addition, the terms “connected” and “coupled” are not restricted tophysical or mechanical connections or couplings, and can includeelectrical connections or couplings, whether direct or indirect.

FIG. 1 illustrates a schematic block diagram of an exemplary imagingsystem 100 in accordance with one embodiment of the present disclosure.As shown in FIG. 1, the exemplary imaging system 100, for example, a CT(computed tomography) imaging system may include a gantry 1. The gantry1 has a radiation source 12 that projects an X-ray beam 14 of X-raystoward a detector array 2 on an opposite side of the gantry 1.

The detector array 2 may be formed by a plurality of detectors 20 whichtogether sense the projection beams 14 that pass through an object 200including multiple materials, such as a patient. Each detector 20 mayproduce an electrical signal that represents the total intensity of eachprojection beam 14 of the X-rays passing through the object 200. Thedetector array 2 may detect a total intensity of single-energy X-rayspassing through the object 200, and may also detect a total intensity ofeach of multi-energy X-rays such as dual energy X-rays, which may beknown as intensity series of multi-energy X-rays.

During a scan to acquire projection data relating to the detectedX-rays, the gantry 1 and the components mounted thereon may rotate abouta center of rotation 10.

Rotation of the gantry 1 and operation of the radiation source 12 may begoverned by a control mechanism 3 of the CT imaging system 100. Thecontrol mechanism 3 may include a radiation controller 31 that providespower and timing signals to the radiation source 12 and a gantry motorcontroller 32 that controls the rotational speed and position of thegantry 1. A data acquisition system (DAS) 33 in the control mechanism 3may sample analog data from the plurality of detectors 20 and convertthe analog data to digital signals for subsequent processing.

A computer 4 may also receive commands and scanning parameters from anoperator via an operator console 6. The operator supplied commands andparameters are used by the computer 4 to provide control signals andinformation to the DAS 33, the radiation controller 31, and the gantrymotor controller 32. In addition, the computer 4 may operate a tablemotor controller 52 which controls a motorized table 51 to position theobject 200 in the gantry 1. The motorized table 51 may move portions ofthe object 200 through an opening (not labeled) of the gantry 1.

The computer 4 may receive sampled and digitized radiation data from theDAS 33, and perform corresponding processing to reconstruct an X-rayimage volume. An associated display 7 allows the operator to observe thereconstructed image I_(mg) and other data from the computer 4. Thecomputer 4 may store the reconstructed image I_(mg) in a storage device8.

The computer 4 of the present disclosure may obtain basis materialinformation of the multiple materials based on the detected totalintensity of the X-rays. Obtaining the basis material information of themultiple materials may include obtaining projection data of at least oneof a path length, an integral of a linear attenuation coefficient, andan integral of a density distribution of each of the multiple materialsfor each projection beam 14 of the X-rays.

Alternatively, the computer 4 of the present disclosure may obtain basiscomponent information of photon-electric absorption basis component andCompton scattering basis component of the object 200 based on thedetected total intensity of the X-rays. The basis component informationof photon-electric absorption basis component and Compton scatteringbasis component of the object 200 may be obtained from the materialdecomposition.

The detected total intensity of the X-rays mentioned in the presentdisclosure should be intended to include the detected total intensity ofsingle-energy X-rays, or the detected total intensity of each ofmulti-energy X-rays (i.e. intensity series of multi-energy X-rays).

Hereinafter, how the computer 4 obtains at least one set of basisinformation of the basis material information and the basis componentinformation based on the detected total intensity of the X-rays will bedescribed in detail with reference to FIGS. 5-6.

FIG. 5 illustrates one embodiment of obtaining the at least one set ofbasis information. In block B51 of FIG. 5, the total intensity of eachof multi-energy X-rays passing through the object 200 comprising themultiple materials may be detected by the detector 20. As an example,the detected multiple total intensities (also known as intensity series)of the multi-energy X-rays may include dual energy X-ray measurementscomprising low-energy X-ray measurements and high-energy X-raymeasurements. Specifically, the detector 20 may detect a total intensityof low-energy X-rays passing through the object 200 comprising themultiple materials, and detecting a total intensity of high-energyX-rays passing through the object 200 comprising the multiple materials.

In an optional block B52, a necessary data conversion and calibrationmay be performed for the detected total intensity of each of themulti-energy X-rays. For example, a data conversion and calibration maybe performed for the total intensity of the low-energy X-rays, and adata conversion and calibration may be performed for the total intensityof the high-energy X-rays.

In block B53, a material decomposition may be performed based on thedetected total intensity of each of the multi-energy X-rays. Forexample, the material decomposition may be performed based on thedetected total intensity of the low-energy X-rays and the detected totalintensity of the high energy X-ray. In an embodiment where block B52 isincluded, the material decomposition process may be performed based onthe calibrated total intensity of the low-energy X-rays and thecalibrated total intensity of the high-energy X-rays.

In block B54, the basis material information of the multiple materialsor the basis component information of the object 200 may be obtainedafter the material decomposition of block B53.

FIG. 6 illustrates another embodiment of obtaining the basis materialinformation of the multiple materials. In block B61 of FIG. 6, atemporary image reconstruction may be performed based on the detectedtotal intensity I_(t).

In block B62, the multiple materials may be segmented based on thetemporary image reconstruction.

In block B63, images of the segmented multiple materials may bereprojected so as to obtain projection data, path lengths or path lengthsequences for the multiple materials. The projection data, the pathlengths or the path length sequences for the multiple materials mayrepresent the basis material information of the multiple materials.

The basis material information of the multiple materials may compriseprojection data, a path length or a path length sequence of each of themultiple materials for each projection beam 14 of the X-rays. In yetanother embodiment, the projection data, the path length or the pathlength sequence of each of the multiple materials for each projectionbeam 14 of the X-rays may also be obtained from direct segmentation ofprojection data of the detected total intensity I_(t).

The computer 4 may perform a scatter correction using the basis materialinformation or the basis component information after obtaining the basismaterial information of the multiple materials or the basis componentinformation of photon-electric absorption basis component and Comptonscattering basis component. The scatter correction performed by usingthe basis component information is similar to the scatter correctionperformed by using the basis material information.

Hereinafter, how the computer 4 performs the scatter correction usingthe basis material information of the multiple materials or the basiscomponent information of the object 200 will be described in detail withreference to FIGS. 2-3.

FIG. 2 illustrates a schematic block diagram of modules executing in thecomputer 4 in accordance with one embodiment of the present disclosure.As shown in FIG. 2, the computer 4 may include a scatter model 41 and ascatter intensity estimation module 44. In one embodiment, the scattermodel 41 may be in association with the basis material information ofthe multiple materials. In this embodiment, the multiple materials maybe characterized by a low effective atomic number material and a higheffective atomic number material. The low effective atomic numbermaterial may for example include a soft tissue. The high effectiveatomic number material may for example include at least one of bone, ametal and a contrast agent such as iodine. Alternatively, in theembodiment using the basis component information, the scatter model 41may be in association with the basis component information ofphoto-electric absorption basis component and Compton scattering basiscomponent of the object 200.

The scatter intensity estimation module 44 may use a scatter model 41according to the obtained basis material information of the multiplematerials and the detected total intensity of the X-rays I_(t) toestimate the scatter intensity component I_(sc). The basis materialinformation of the multiple materials may include projection data of thebasis material information used to characterize the multiple materialsalong each projection beam 14 of the X-rays. Alternatively, in theembodiment using the basis component information, the scatter intensityestimation module 44 may use the scatter model 41 according to theobtained basis component information of photo-electric absorption basiscomponent and Compton scattering basis component of the object 200 andthe detected total intensity of the X-rays I_(t) to estimate the scatterintensity component I_(Sc).

The scatter model 41 may be established based on the detected totalintensity I_(t) and the obtained projection data of the basis materialinformation of each material along each projection beam 14.

For example, in one embodiment, the scatter model 41 may include thefollowing equation:

$\begin{matrix}{I_{sc} = {{KI}_{t}^{f_{1}{({p_{l},p_{h}})}}\left( {- {\log\left( \frac{I_{t}}{I_{0}} \right)}} \right)}^{f_{2}{({p_{l},p_{h}})}}} & (1)\end{matrix}$

where I_(sc) represents the estimated scatter intensity component, I_(t)represents the detected total intensity of the X-rays in the scan of theobject 200, I₀ represents a detected total intensity of the X-rays in anair scan without the object 200, p_(l) represents projection data forthe low effective atomic number material, p_(h) represents projectiondata for the high effective atomic number material, f₁ and f₂ representfunctions of p_(l) and p_(h), K represents a constant scaling factor,and p_(l) and p_(h) may characterize the basis material information ofthe low and the high effective atomic number materials.

Thus, the scatter intensity estimation module 44 may use the detectedtotal intensity I_(t), the detected total intensity I₀ without theobject 200, and the projection data p_(l) and p_(h) for the low and thehigh effective atomic number materials from the scatter model 41 toestimate the scatter intensity component I_(sc).

In another embodiment, the scatter model 41 may include the followingequation:

$\begin{matrix}{I_{sc} = {{KI}_{t}^{a_{1} + {a_{2}\frac{p_{h}}{p_{l}}}}\left( {- {\log\left( \frac{I_{t}}{I_{0}} \right)}} \right)}^{b_{1} + {b_{2}\frac{p_{h}}{p_{l}}}}} & (2)\end{matrix}$

Where K, a₁, a₂, b₁ and b₂ are tuned parameters for the low and the higheffective atomic number materials respectively.

In still another embodiment, the scatter model 41 may include thefollowing equation:I _(sc) =K _(l) I _(t) ^(a) ^(l) p _(l) ^(b) ^(l) +K _(h) I _(t) ^(a)^(h) p _(h) ^(b) ^(h)   (3)

Where K₁, a₁, b₁, K_(h), a_(h) and b_(h) are tuned parameters for thelow and the high effective atomic number materials respectively.

The equations (1)-(3) above are only illustrative examples of thescatter model 41. However, the scatter model 41 of the presentdisclosure should be not limited hereinto. The scatter model 41incorporating the material information would be covered in theprotection scope of the present disclosure.

The computer 4 may include a correction module 45. The correction module45 may receive the estimated scatter intensity component I_(sc) and thedetected total intensity I_(t), and obtain an intensity estimate I_(c)of primary X-rays incident on a detector 20 based on the detected totalintensity I_(t) and the estimated scatter intensity component I_(sc). Asan example, the primary intensity estimate I_(c), may be obtained bysubtracting the estimated scatter intensity component I_(sc) from thedetected total intensity I_(t).

The computer 4 may include an image reconstructor 47. The imagereconstructor 47 may receive the primary intensity estimate I_(c),output by the correction module 45, and may reconstruct an X-ray imageI_(mg) using the obtained primary intensity estimate I_(c).

A material decomposition process with improved accuracy can be performedagain to provide projection data of the basis material information ofeach material for image reconstruction.

FIG. 3 illustrates a schematic block diagram of modules executing in thecomputer 4 in accordance with another embodiment of the presentdisclosure. As shown in FIG. 3, the computer 4 may include a weightingmodel 42, single-material scatter models 43 and a scatter intensityestimation module 44.

The scatter intensity estimation module 44 may use a weighting model 42to weight the basis material information of the multiple materials (forexample, the obtained projection data of each of the multiplematerials), determine a scatter intensity component of each material,I_(sc,i), based on individual single-material scatter models 43 for eachmaterial, weight the scatter intensity component of each material,I_(sc,i), determined by the single-material scatter models 43 with theweighted projection data of each material, and estimate the scatterintensity component I_(sc) of the detected X-rays based on the weightedscatter intensity component of each material.

In one embodiment, the weighting model 42 may include the followingequations:

$\begin{matrix}{{w_{i} = \frac{p_{i}^{\prime}}{\sum\limits_{i}p_{i}^{\prime}}}\;} & (4) \\{p_{i}^{\prime} = {p_{i} \times {\sum\limits_{E}\left( {S_{E} \times {f\left( {ɛ_{{sc},i,E},ɛ_{i,E}} \right)}} \right)}}} & (5)\end{matrix}$

Where w_(i) represents a weighting factor of each material determined byequation (4), i represents the index of material, p_(i)′ represents aweighted projection data of each material determined by equation (5),p_(i) represents the projection data of each material obtained in thematerial decomposition process, S_(E) represents an X-ray intensity ofthe spectrum at energy E of the X-rays, ε_(sc,i,E) represents a sum ofcross-sections of Compton scattering and Rayleigh scattering of eachmaterial at energy E, ε_(i,E) represents a total cross-section of X-rayprocesses of each material at energy E, and f represents a function ofε_(sc,i,E) and ε_(i,E).

The individual single-material scatter models 43 for each material mayinclude the following equation:

$\begin{matrix}{I_{{sc},i} = {k_{i}{I_{t}^{m_{i}}\left( {- {\log\left( \frac{I_{t}}{I_{0}} \right)}} \right)}^{n_{i}}}} & (6)\end{matrix}$

Where I_(sc,i) represents a scatter intensity component of each materialobtained by individual single-material scatter models 43 for eachmaterial, I_(t) represents the detected total intensity of the X-rays inthe scan of the object 200, I₀ represents a detected total intensity ofthe X-rays in an air scan without the object 200, and k_(i), m_(i) andn_(i) are tuned parameters for the single-material scatter models 43.

The scatter intensity estimation module 44 may receive the detectedtotal intensity I_(t), the obtained basis material information of themultiple materials, the weighting factor w_(i) of each material and thescatter intensity component of each material, I_(sc,i), obtained byindividual single-material scatter models 43 for each material, andestimate the scatter intensity component I_(sc) according to thefollowing equation:I _(sc)=Σ_(i)(I _(sc,i) ×w _(i))  (7)

Because the basis component information and the basis materialinformation can be converted to each other using some simple transferfunction, the method executed in modules of FIG. 3 may be similarlyapplied to the basis component information.

The system 100 of the present disclosure may perform the scattercorrection using the basis material information of the multiplematerials or the basis component information of the object 200 and solvethe multiple material problem of fast scatter estimation and correction.Therefore, the system 100 of the present disclosure may reduce greatlyor even eliminate artifacts caused by the scatter and improve the imagequality and quantitative measurement of Hounsfield Units (HU) of thereconstructed images.

The present disclosure may further provide a signal processing method.FIG. 4 illustrates a flow chart of an exemplary signal processing methodin accordance with an embodiment of the present disclosure.

As shown in FIG. 4, in block B41, a total intensity or intensity seriesI_(t) of X-rays may be detected passing through an object 200 comprisingmultiple materials with single or multiple scans at single or multipleenergies.

In block B42, at least one set of basis information of basis materialinformation of the multiple materials and basis component information ofphoton-electric absorption basis component and Compton scattering basiscomponent of the object 200 may be obtained. The basis materialinformation of the multiple materials may be obtained for example withreference to the methods shown in FIGS. 5-6. The basis materialinformation of the multiple materials may include projection data of atleast one of a path length, an integral of the linear attenuationcoefficient, and an integral of the density distribution of each of themultiple materials along each projection beam 14 of the X-rays. Thebasis component information of photon-electric absorption basiscomponent and Compton scattering basis component of the object 200 maybe obtained from the material decomposition.

In block B43, a scatter intensity component I_(sc) of the detectedX-rays may be estimated based on the at least one set of basisinformation and the detected total intensity I_(t).

In block B44, an intensity estimate of primary X-rays I_(c), incident ona detector 20 may be obtained based on the detected total intensityI_(t) and the estimated scatter intensity component I_(sc). Theintensity estimate of primary X-rays I_(c) may be obtained bysubtracting the estimated scatter intensity component I_(sc) from thedetected total intensity I_(t).

In block B45, an X-ray image I_(mg) may be reconstructed using theobtained primary intensity estimate I_(c).

The method of the present disclosure may perform the scatter correctionusing the basis material information of the multiple materials or thebasis component information of the object 200, and solve the multiplematerial problems of fast scatter estimation and correction. Therefore,the method of the present disclosure may reduce greatly or eliminateartifacts caused by the scatter and improve the image quality andquantitative measurement of Hounsfield Units (HU) of the reconstructedimages.

While steps of the signal processing methods in accordance withembodiments of the present disclosure are illustrated as functionalblocks, the order of the blocks and the separation of the steps amongthe various blocks shown in FIGS. 4-6 are not intended to be limiting.For example, the blocks may be performed in a different order and a stepassociated with one block may be combined with one or more other blocksor may be sub-divided into a number of blocks.

While the disclosure has been illustrated and described in typicalembodiments, it is not intended to be limited to the details shown,since various modifications and substitutions can be made withoutdeparting in any way from the spirit of the present disclosure. As such,further modifications and equivalents of the disclosure herein disclosedmay occur to persons skilled in the art using no more than routineexperimentation, and all such modifications and equivalents are believedto be within the spirit and scope of the disclosure as defined by thefollowing claims.

What is claimed is:
 1. A signal processing method, comprising: detectinga total intensity of X-rays passing through an object comprisingmultiple materials via a detector of a computed tomography system;obtaining, via a computer, at least one set of basis information ofbasis material information of the multiple materials and basis componentinformation of photon-electric absorption basis component and Comptonscattering basis component of the object, wherein obtaining the basismaterial information of the multiple materials comprises obtainingprojection data of the basis material information used to characterizeeach of the multiple materials along each projection beam of the X-rays;estimating, via the computer, a scatter intensity component of thedetected X-rays based on the at least one set of basis information andthe detected total intensity; and obtaining, via the computer, anintensity estimate of primary X-rays incident on a detector based on thedetected total intensity and the estimated scatter intensity component;wherein estimating the scatter intensity component comprises using aweighting model to weight the obtained projection data of each material,determining a scatter intensity component of each material based onindividual single-material scatter models for each material, weightingthe scatter intensity component of each material determined by thesingle-material scatter models with the weighted projection data of eachmaterial, and estimating the scatter intensity component of the detectedX-rays based on the weighted scatter intensity component of eachmaterial.
 2. The method of claim 1, wherein obtaining the basis materialinformation of the multiple materials comprises obtaining projectiondata of at least one of a path length, an integral of a linearattenuation coefficient, and an integral of a density distribution ofeach of the multiple materials for each projection beam of the X-rays.3. The method of claim 2, wherein obtaining the projection data of atleast one of a path length, an integral of a linear attenuationcoefficient, and an integral of a density distribution of each of themultiple materials for each projection beam of the X-rays comprisesperforming a material decomposition process.
 4. The method of claim 1,comprising reconstructing, via the computer, an X-ray image based on theintensity estimate.
 5. The method of claim 1, comprising detecting anadditional total intensity of X-rays passing through air, and whereineach individual single-material scatter model utilizes the detectedadditional total intensity in estimating the scatter intensitycomponent.
 6. The method of claim 1, wherein each individualsingle-material scatter model is established based on at least thedetected total intensity.
 7. The method of claim 1, wherein obtainingthe basis material information of the multiple materials comprisesobtaining projection data, a path length or a path length sequence ofeach of the multiple materials for each projection beam of the X-rays,and obtaining the projection data, the path length or the path lengthsequence of each of the multiple materials for each projection beam ofthe X-rays comprises performing a temporary image reconstruction basedon the detected total intensity, segmenting the multiple materials basedon the temporary image reconstruction, and reprojecting images of thesegmented multiple materials to obtain the projection data, the pathlengths or the path length sequences for the multiple materials.
 8. Themethod of claim 1, wherein obtaining the basis material information ofthe multiple materials comprises obtaining projection data, a pathlength or a path length sequence of each of the multiple materials foreach projection beam of the X-rays from direct segmentation ofprojection data of the detected total intensity.
 9. The method of claim1, wherein detecting the total intensity of the X-rays passing throughthe object comprising the multiple materials comprises detecting a totalintensity of low-energy X-rays passing through the object comprising themultiple materials, and detecting a total intensity of high-energyX-rays passing through the object comprising the multiple materials, andwherein obtaining the basis material information of the multiplematerials comprises performing a material decomposition process based onthe detected total intensity of the low-energy X-rays and the detectedtotal intensity of the high energy X-ray.
 10. The method of claim 9,wherein before performing the material decomposition process, the methodfurther comprises performing data conversion and calibration for thetotal intensity of the low-energy X-rays, and performing data conversionand calibration for the total intensity of the high-energy X-rays, andwherein performing the material decomposition process is based on thecalibrated total intensity of the low-energy X-rays and the calibratedtotal intensity of the high-energy X-rays.
 11. The method of claim 1,wherein the multiple materials is characterized by a low effectiveatomic number material and a high effective atomic number material. 12.The method of claim 11, wherein the low effective atomic number materialcomprises a soft tissue, and the high effective atomic number comprisesat least one of bone, a metal and a contrast agent.
 13. A computedtomography imaging system, comprising: a detector configured to detect atotal intensity of X-rays passing through an object comprising multiplematerials; and a computer configured to obtain at least one set of basisinformation of basis material information of the multiple materials andbasis component information of photon-electric absorption basiscomponent and Compton scattering basis component of the object, estimatea scatter intensity component of the detected X-rays based on the atleast one set of basis information and the detected total intensity, andobtain an intensity estimate of primary X-rays incident on the detectorbased on the detected total intensity and the estimated scatterintensity component, wherein the computer is configured to obtain thebasis material information of the multiple materials by obtainingprojection data of the basis material information used to characterizeeach of the multiple materials along each projection beam of the X-rays;wherein the computer is configured to estimate the scatter intensitycomponent by using a weighting model to weight the obtained projectiondata of each material, determining a scatter intensity component of eachmaterial based on individual single-material scatter models for eachmaterial, weighting the scatter intensity component of each materialdetermined by the single-material scatter models with the weightedprojection data of each material, and estimating the scatter intensitycomponent of the detected X-rays based on the weighted scatter intensitycomponent of each material.
 14. The computed tomography imaging systemof claim 13, wherein the computer is configured to reconstruct an X-rayimage based on the intensity estimate.
 15. The computed tomographyimaging system of claim 13, wherein the computer is configured forperforming a material decomposition process for the detected totalintensity of the X-rays to obtain the projection data of at least one ofa path length, an integral of the linear attenuation coefficient, and anintegral of the density distribution of each of the multiple materialsalong each projection beam of the X-rays.
 16. The computed tomographyimaging system of claim 13, wherein the computer is configured forobtaining projection data, a path length or a path length sequence ofeach of the multiple materials for each projection beam of the X-rays,and obtaining the projection data, the path length or the path lengthsequence of each of the multiple materials for each projection beam ofthe X-rays comprises: performing a temporary image reconstruction basedon the detected total intensity; segmenting the multiple materials basedon the temporary image reconstruction; and reprojecting images of thesegmented multiple materials to obtain the projection data, the pathlengths or the path length sequences for the multiple materials.
 17. Thecomputed tomography imaging system of claim 13, wherein the computer isconfigured for performing a material decomposition process for thedetected total intensity of the X-rays to obtain projection data of thebasis material information of each material for each projection beam ofthe X-rays.
 18. The computed tomography imaging system of claim 13,wherein the multiple materials is characterized by a low effectiveatomic number material and a high effective atomic number material. 19.The computed tomography imaging system of claim 18, wherein the loweffective atomic number material comprises a soft tissue, and the higheffective atomic number comprises at least one of bone, a metal and acontrast agent.
 20. The computed tomography imaging system of claim 13,wherein the detector is configured to detect an additional totalintensity of X-rays passing through air, and wherein each individualsingle-material scatter model is configured to utilize the detectedadditional total intensity in estimating the scatter intensitycomponent.